模拟在线社会反应:刺激/反应视角

Huajie Shao, T. Abdelzaher, Jiawei Han, Minhao Jiang, Yuning Mao, Yu Meng, Wenda Qiu, Dachun Sun, Ruijie Wang, Chaoqi Yang, Zhenzhou Yang, Xinyang Zhang, Yu Zhang, Sam Cohen, James Flamino, G. Korniss, O. Malik, Aamir Mandviwalla, B. Szymanski, Lake Yin
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引用次数: 0

摘要

本文描述了一种模拟响应外部事件而发生的在线社交媒体活动的方法。大量的社交媒体模拟器模拟了在线社交网络上的信息传播。然而,信息级联并非起源于真空。相反,它们通常源于对网络媒体外部事件的反应。因此,为了预测社交媒体上的活动,必须研究外部刺激与在线社会反应之间的关系。本文提出了一个模拟管道,其特征是刺激/反应模型,描述了社会系统如何对与其相关的外部事件作出反应。通过两个实例验证了不同模型的保真度。其中一项研究调查了委内瑞拉选举危机事件在网上的反应。另一项调查是对中巴经济走廊(CPEC)发展的在线反应。这些案例研究表明,简单的宏观刺激/反应模型可以准确地预测总体在线趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulating Online Social Response: A Stimulus/Response Perspective
The paper describes a methodology for simulating online social media activities that occur in response to external events. A large number of social media simulators model information diffusion on online social networks. However, information cascades do not originate in vacuum. Rather, they often originate as a reaction to events external to the online medium. Thus, to predict activity on the social medium, one must investigate the relation between external stimuli and online social responses. The paper presents a simulation pipeline that features stimulus/response models describing how social systems react to external events of relevance to them. Two case studies are presented to test the fidelity of different models. One investigates online responses to events in the Venezuela election crisis. The other investigates online responses to developments of the China Pakistan Economic Corridor (CPEC). These case studies indicate that simple macroscopic stimulus/response models can accurately predict aggregate online trends.
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